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Log-sigmoid nonlinear Lagrange method for nonlinear optimization problems over second-order cones. (English) Zbl 1173.65043

This paper analyzes the rate of local convergence of the Log-Sigmoid nonlinear Lagrangian method for nonconvex nonlinear second-order cone programming. Under the componentwise strict complementarity condition, a constraint nondegeneracy condition and a second-order sufficient condition, the authors show that the sequence of iteration points generated by the proposed method locally converges to a local solution when the penalty parameter is less than a treshold and the error bound of solution is proportional to the penalty parameter. Finally, numerical results show the efficiency of the method.

MSC:

65K05 Numerical mathematical programming methods
90C26 Nonconvex programming, global optimization
90C30 Nonlinear programming
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